Raffaele Marino

Orcid: 0000-0002-2311-4380

According to our database1, Raffaele Marino authored at least 24 papers between 2015 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Exact Fixed-Point Constraints in Neural-ODEs with Provable Universality.
CoRR, May, 2026

Benchmarking Graph Neural Networks in Solving Hard Constraint Satisfaction Problems.
CoRR, February, 2026

2025
Daydreaming Hopfield Networks and their surprising effectiveness on correlated data.
Neural Networks, 2025

Learning in Wilson-Cowan Model for Metapopulation.
Neural Comput., 2025

Deterministic versus stochastic dynamical classifiers: opposing random adversarial attacks with noise.
Mach. Learn. Sci. Technol., 2025

2024
Phase transitions in the mini-batch size for sparse and dense two-layer neural networks.
Mach. Learn. Sci. Technol., March, 2024

Stable attractors for neural networks classification via ordinary differential equations (SA-nODE).
Mach. Learn. Sci. Technol., 2024

Fast Analysis of the OpenAI O1-Preview Model in Solving Random K-SAT Problem: Does the LLM Solve the Problem Itself or Call an External SAT Solver?
CoRR, 2024

Automatic Input Feature Relevance via Spectral Neural Networks.
CoRR, 2024

A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms.
CoRR, 2024

The Garden of Forking Paths: Observing Dynamic Parameters Distribution in Large Language Models.
CoRR, 2024

2023
Large Independent Sets on Random d-Regular Graphs with Fixed Degree d.
Comput., October, 2023

Solving Non-linear Kolmogorov Equations in Large Dimensions by Using Deep Learning: A Numerical Comparison of Discretization Schemes.
J. Sci. Comput., 2023

Complex Recurrent Spectral Network.
CoRR, 2023

A Bridge between Dynamical Systems and Machine Learning: Engineered Ordinary Differential Equations as Classification Algorithm (EODECA).
CoRR, 2023

Where do hard problems really exist?
CoRR, 2023

Stochastic Gradient Descent-like relaxation is equivalent to Glauber dynamics in discrete optimization and inference problems.
CoRR, 2023

Phase transitions in the mini-batch size for sparse and dense neural networks.
CoRR, 2023

2022
Hard Optimization Problems have Soft Edges.
CoRR, 2022

2021
Learning from survey propagation: a neural network for MAX-E-3-SAT.
Mach. Learn. Sci. Technol., September, 2021

Nonequilibrium Monte Carlo for unfreezing variables in hard combinatorial optimization.
CoRR, 2021

2020
Large independent sets on random d-regular graphs with d small.
CoRR, 2020

2018
Revisiting the Challenges of MaxClique.
CoRR, 2018

2015
The Backtracking Survey Propagation Algorithm for Solving Random K-SAT Problems.
CoRR, 2015


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